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Terrorist Group Cooperation and Longevity

Why do some terrorist groups survive considerably longer than others? The literature is just beginning to address this important question in a systematic manner. Additionally, and as with most studies of terrorism, longevity studies have ignored the possibility of interactions between terrorist groups. This article attempts to address these two gaps in the literature: the incomplete understanding of terrorist group survival and the tendency to assume that terrorist groups act independently. In spite of risks associated with cooperation, I argue that it should help involved terrorist groups mitigate mobilization concerns. More importantly, the impact of cooperation is conditioned by attributes of the country in which a terrorist group operates. Using new global data on terrorist groups between 1987 and 2005, I show that cooperation has the strongest effect on longevity in states where groups should have a harder time operating—more capable states and less democratic states. Interestingly, a group's number of relationships is more important than to whom the group is connected.


Phillips, Brian J. "Terrorist Group Cooperation and Longevity." International Studies Quarterly (2013).

http://dx.doi.org/10.1111/isqu.12073

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Dynamics and spatial distribution of global nighttime lights

Dynamics and spatial distribution of global nighttime lights | Papers | Scoop.it

Using open source data, we observe the fascinating dynamics of nighttime light. Following a global economic regime shift, the planetary center of light can be seen moving eastwards at a pace of about 60 km per year. Introducing spatial light Gini coefficients, we find a universal pattern of human settlements across different countries and see a global centralization of light. Observing 160 different countries we document the expansion of developing countries, the growth of new agglomerations, the regression in countries suffering from demographic decline and the success of light pollution abatement programs in western countries.


Dynamics and spatial distribution of global nighttime lights
Peter Cauwels, Nicola Pestalozzi and Didier Sornette

EPJ Data Science 2014, 3:2  http://dx.doi.org/10.1140/epjds19


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Exploring Martian Habitability

Exploring Martian Habitability | Papers | Scoop.it

In the search for organic remnants of past life, it is enormously helpful to have a paradigm to guide exploration. This begins with assessing habitability: Was the former environment supportive of life? If so, was it also conducive to preservation of organism remains, specifically large organic molecules? Five articles presented in the 24 January edition of Science describe the detection at Gale crater of a system of ancient environments that would have been habitable by chemoautotrophic microorganisms. A sixth article details a more ancient and also potentially habitable environment detected in Noachian age (>~3.7 billion years) rocks at Meridiani Planum. A seventh article describes the present radiation environment on the surface of Mars at Gale crater.


Exploring Martian Habitability

http://www.sciencemag.org/site/extra/curiosity/index.xhtml

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The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan

While studies of aging are widely framed in terms of their demarcation of degenerative processes, the brain provides a unique opportunity to uncover the adaptive effects of getting older. Though intuitively reasonable, that life-experience and wisdom should reside somewhere in human cortex, these features have eluded neuroscientific explanation. The present study utilizes a “Bayesian Brain” framework to motivate an analysis of cortical circuit processing. From a Bayesian perspective, the brain represents a model of its environment and offers predictions about the world, while responding, through changing synaptic strengths to novel interactions and experiences. We hypothesized that these predictive and updating processes are modified as we age, representing an optimization of neuronal architecture. Using novel sensory stimuli we demonstrate that synaptic connections of older brains resist trial by trial learning to provide a robust model of their sensory environment. These older brains are capable of processing a wider range of sensory inputs – representing experienced generalists. We thus explain how, contrary to a singularly degenerative point-of-view, aging neurobiological effects may be understood, in sanguine terms, as adaptive and useful.


Moran RJ, Symmonds M, Dolan RJ, Friston KJ (2014) The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan. PLoS Comput Biol 10(1): e1003422. http://dx.doi.org/10.1371/journal.pcbi.1003422

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From mobile phone data to the spatial structure of cities

Pervasive infrastructures, such as cell phone networks, enable to capture large amounts of human behavioral data but also provide information about the structure of cities and their dynamical properties. In this article, we focus on these last aspects by studying phone data recorded during 55 days in 31 Spanish metropolitan areas. We first define an urban dilatation index which measures how the average distance between individuals evolves during the day, allowing us to highlight different types of city structure. We then focus on hotspots, the most crowded places in the city. We propose a parameter free method to detect them and to test the robustness of our results. The number of these hotspots scales sublinearly with the population size, a result in agreement with previous theoretical arguments and measures on employment datasets. We study the lifetime of these hotspots and show in particular that the hierarchy of permanent ones, which constitute the "heart" of the city, is very stable whatever the size of the city. The spatial structure of these hotspots is also of interest and allows us to distinguish different categories of cities, from monocentric and "segregated" where the spatial distribution is very dependent on land use, to polycentric where the spatial mixing between land uses is much more important. These results point towards the possibility of a new, quantitative classification of cities using high resolution spatio-temporal data.


From mobile phone data to the spatial structure of cities
Thomas Louail, Maxime Lenormand, Oliva García Cantú, Miguel Picornell, Ricardo Herranz, Enrique Frias-Martinez, José J. Ramasco, Marc Barthelemy

http://arxiv.org/abs/1401.4540

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Efficient detection of contagious outbreaks in massive metropolitan encounter networks

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme --- a simple, but universal strategy requiring only local information --- and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.


Efficient detection of contagious outbreaks in massive metropolitan encounter networks
Lijun Sun, Kay W. Axhausen, Der-Horng Lee, Manuel Cebrian

http://arxiv.org/abs/1401.2815

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A logic for reasoning about ambiguity

Standard models of multi-agent modal logic do not capture the fact that information is often ambiguous, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different semantics that capture different assumptions about the agentsʼ beliefs regarding whether or not there is ambiguity. We examine the expressive power of logics of ambiguity compared to logics that cannot model ambiguity, with respect to the different semantics that we propose.


A logic for reasoning about ambiguity
Joseph Y. Halpern, Willemien Kets

Artificial Intelligence
In Press, Accepted Manuscript

http://dx.doi.org/10.1016/j.artint.2013.12.003

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Who is Dating Whom: Characterizing User Behaviors of a Large Online Dating Site

Online dating sites have become popular platforms for people to look for potential romantic partners. It is important to understand users' dating preferences in order to make better recommendations on potential dates. The message sending and replying actions of a user are strong indicators for what he/she is looking for in a potential date and reflect the user's actual dating preferences. We study how users' online dating behaviors correlate with various user attributes using a large real-world dateset from a major online dating site in China. Many of our results on user messaging behavior align with notions in social and evolutionary psychology: males tend to look for younger females while females put more emphasis on the socioeconomic status (e.g., income, education level) of a potential date. In addition, we observe that the geographic distance between two users and the photo count of users play an important role in their dating behaviors. Our results show that it is important to differentiate between users' true preferences and random selection. Some user behaviors in choosing attributes in a potential date may largely be a result of random selection. We also find that both males and females are more likely to reply to users whose attributes come closest to the stated preferences of the receivers, and there is significant discrepancy between a user's stated dating preference and his/her actual online dating behavior. These results can provide valuable guidelines to the design of a recommendation engine for potential dates.


Who is Dating Whom: Characterizing User Behaviors of a Large Online Dating Site
Peng Xia, Kun Tu, Bruno Ribeiro, Hua Jiang, Xiaodong Wang, Cindy Chen, Benyuan Liu, Don Towsley

http://arxiv.org/abs/1401.5710

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Urbansocial's curator insight, July 14, 2014 11:41 AM

Urban Social - Online dating for sociable singles www.urbansocial.com

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To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets | Papers | Scoop.it

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.


To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets
J. Borondo, F. Borondo, C. Rodriguez-Sickert & C. A. Hidalgo

Scientific Reports 4, Article number: 3784 http://dx.doi.org/10.1038/srep03784

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Computer science: The learning machines

Three years ago, researchers at the secretive Google X lab in Mountain View, California, extracted some 10 million still images from YouTube videos and fed them into Google Brain — a network of 1,000 computers programmed to soak up the world much as a human toddler does. After three days looking for recurring patterns, Google Brain decided, all on its own, that there were certain repeating categories it could identify: human faces, human bodies and … cats.

Google Brain's discovery that the Internet is full of cat videos provoked a flurry of jokes from journalists. But it was also a landmark in the resurgence of deep learning: a three-decade-old technique in which massive amounts of data and processing power help computers to crack messy problems that humans solve almost intuitively, from recognizing faces to understanding language.


http://www.nature.com/news/computer-science-the-learning-machines-1.14481

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Open Learning at a Distance: Lessons for Struggling MOOCs

Free education is changing how people think about learning online. The rise of Massive Open Online Courses (MOOCs) (1) shows that large numbers of learners can be reached. It also raises questions as to how effectively they support learning (2). There is a timeliness in the introduction of MOOCs, reflecting the right combination of online systems, interest from good teachers in reaching more learners, and banks of digital resources, predicted as a “perfect storm of innovation” (3). However, learning at scale, at a distance, is not a new phenomenon. Seeing MOOCs narrowly as a technology that expands access to in-classroom teaching can miss opportunities. Drawing on decades of lessons learned, we set out aims to help spur innovation in science education.


Open Learning at a Distance: Lessons for Struggling MOOCs
Patrick McAndrew, Eileen Scanlon

Science 20 December 2013:
Vol. 342 no. 6165 pp. 1450-1451
http://dx.doi.org/10.1126/science.1239686

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From funding agencies to scientific agency

The traditional peer review system for grant proposals is not always optimal. A new crowdfunding proposal based on advances in technology and mathematics could improve efficiency while retaining peer judgement.


From funding agencies to scientific agency
Collective allocation of science funding as an alternative to peer review
Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Börner

EMBO reports
Early View

http://dx.doi.org/10.1002/embr.201338068

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Urban Mobility Scaling: Lessons from `Little Data'

Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper attempts to complement this research by looking at a category-rich mobility data set. In order to shed light on the impact of categories, as a case study, we use conventionally collected German mobility data. In contrast to `check-in'-based data, our results are not biased by Euclidean distance approximations. In our analysis, we show that aggregation can hide crucial differences between trip length distributions, when subdivided by categories. For example, we see that on an urban scale (0 to ~15 km), walking, versus driving, exhibits a highly different scaling exponent, thus universality class. Moreover, mode share and trip length are responsive to day-of-week and time-of-day. For example, in Germany, although driving is relatively less frequent on Sundays than on Wednesdays, trips seem to be longer. In addition, our work may shed new light on the debate between distance-based and intervening-opportunity mechanisms affecting mobility patterns, since mode may be chosen both according to trip length and urban form.


Urban Mobility Scaling: Lessons from `Little Data'
Galen Wilkerson, Ramin Khalili, Stefan Schmid

http://arxiv.org/abs/1401.0207

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Delineating Geographical Regions with Networks of Human Interactions in an Extensive Set of Countries

Delineating Geographical Regions with Networks of Human Interactions in an Extensive Set of Countries | Papers | Scoop.it

Large-scale networks of human interaction, in particular country-wide telephone call networks, can be used to redraw geographical maps by applying algorithms of topological community detection. The geographic projections of the emerging areas in a few recent studies on single regions have been suggested to share two distinct properties: first, they are cohesive, and second, they tend to closely follow socio-economic boundaries and are similar to existing political regions in size and number. Here we use an extended set of countries and clustering indices to quantify overlaps, providing ample additional evidence for these observations using phone data from countries of various scales across Europe, Asia, and Africa: France, the UK, Italy, Belgium, Portugal, Saudi Arabia, and Ivory Coast. In our analysis we use the known approach of partitioning country-wide networks, and an additional iterative partitioning of each of the first level communities into sub-communities, revealing that cohesiveness and matching of official regions can also be observed on a second level if spatial resolution of the data is high enough. The method has possible policy implications on the definition of the borderlines and sizes of administrative regions.


Sobolevsky S, Szell M, Campari R, Couronné T, Smoreda Z, et al. (2013) Delineating Geographical Regions with Networks of Human Interactions in an Extensive Set of Countries. PLoS ONE 8(12): e81707. http://dx.doi.org/10.1371/journal.pone.0081707

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Elastic Pathing: Your Speed is Enough to Track You

Today people increasingly have the opportunity to opt-in to "usage-based" automotive insurance programs for reducing insurance premiums. In these programs, participants install devices in their vehicles that monitor their driving behavior, which raises some privacy concerns. Some devices collect fine-grained speed data to monitor driving habits. Companies that use these devices claim that their approach is privacy-preserving because speedometer measurements do not have physical locations. However, we show that with knowledge of the user's home location, as the insurance companies have, speed data is sufficient to discover driving routes and destinations when trip data is collected over a period of weeks. To demonstrate the real-world applicability of our approach we applied our algorithm, elastic pathing, to data collected over hundreds of driving trips occurring over several months. With this data and our approach, we were able to predict trip destinations to within 250 meters of ground truth in 10% of the traces and within 500 meters in 20% of the traces. This result, combined with the amount of speed data that is being collected by insurance companies, constitutes a substantial breach of privacy because a person's regular driving pattern can be deduced with repeated examples of the same paths with just a few weeks of monitoring.


Elastic Pathing: Your Speed is Enough to Track You
Bernhard Firner, Shridatt Sugrim, Yulong Yang, Janne Lindqvist

http://arxiv.org/abs/1401.0052

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Entropy and the Predictability of Online Life

Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.


Entropy and the Predictability of Online Life
Roberta Sinatra and Michael Szell

Entropy 2014, 16(1), 543-556; http://dx.doi.org/10.3390/e16010543

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Left Brain, Right Brain: Facts and Fantasies

Handedness and brain asymmetry are widely regarded as unique to humans, and associated with complementary functions such as a left-brain specialization for language and logic and a right-brain specialization for creativity and intuition. In fact, asymmetries are widespread among animals, and support the gradual evolution of asymmetrical functions such as language and tool use. Handedness and brain asymmetry are inborn and under partial genetic control, although the gene or genes responsible are not well established. Cognitive and emotional difficulties are sometimes associated with departures from the “norm” of right-handedness and left-brain language dominance, more often with the absence of these asymmetries than their reversal.


Corballis MC (2014) Left Brain, Right Brain: Facts and Fantasies. PLoS Biol 12(1): e1001767. http://dx.doi.org/10.1371/journal.pbio.1001767

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Localization and centrality in networks

Eigenvector centrality is a widely used measure of the importance of nodes in a network. Here we show that under common conditions the eigenvector centrality displays a localization transition that causes most of the weight of the centrality to concentrate on a small number of nodes in the network and renders the measure useless for most practical purposes. As a remedy, we propose an alternative centrality measure based on the non-backtracking matrix, which gives results closely similar to the standard eigenvector centrality in dense networks where the latter is well behaved, but avoids localization and gives useful results in regimes where the standard centrality fails.


Localization and centrality in networks
Travis Martin, Xiao Zhang, M. E. J. Newman

http://arxiv.org/abs/1401.5093

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Inconstants of Nature

Inconstants of Nature | Papers | Scoop.it

Why should the future resemble the past? Well, for one thing, it always has. But that is itself an observation from the past. As the philosopher David Hume pointed out in the middle of the 18th century, we can’t use our experience in the past to argue that the future will resemble it, without descending into circular logic. What’s more, physicists remain unable to explain why certain fundamental constants of nature have the values that they do, or why those values should remain constant over time.
The question is a troubling one, especially for scientists. For one thing, the scientific method of hypothesis, test, and revision would falter if the fundamental nature of reality were constantly shifting. And scientists could no longer make predictions about the future or reconstructions of the past, or rely on past experiments with complete confidence. But science also has an ace up its sleeve: Unlike philosophy, it can try to measure whether the laws of nature and the constants that parameterize those laws are changing.

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Time domain measures of inter-channel EEG correlations: a comparison of linear, nonparametric and nonlinear measures

Correlations between ten-channel EEGs obtained from thirteen healthy adult participants were investigated. Signals were obtained in two behavioral states: eyes open no task and eyes closed no task. Four time domain measures were compared: Pearson product moment correlation, Spearman rank order correlation, Kendall rank order correlation and mutual information. The psychophysiological utility of each measure was assessed by determining its ability to discriminate between conditions. The sensitivity to epoch length was assessed by repeating calculations with 1, 2, 3, …, 8 s epochs. The robustness to noise was assessed by performing calculations with noise corrupted versions of the original signals (SNRs of 0, 5 and 10 dB). Three results were obtained in these calculations. First, mutual information effectively discriminated between states with less data. Pearson, Spearman and Kendall failed to discriminate between states with a 1 s epoch, while a statistically significant separation was obtained with mutual information. Second, at all epoch durations tested, the measure of between-state discrimination was greater for mutual information. Third, discrimination based on mutual information was more robust to noise. The limitations of this study are discussed. Further comparisons should be made with frequency domain measures, with measures constructed with embedded data and with the maximal information coefficient.


Time domain measures of inter-channel EEG correlations: a comparison of linear, nonparametric and nonlinear measures
J. D. Bonita, L. C. C. Ambolode II, B. M. Rosenberg, C. J. Cellucci, T. A. A. Watanabe, P. E. Rapp, A. M. Albano

Cognitive Neurodynamics
February 2014, Volume 8, Issue 1, pp 1-15,

http://dx.doi.org/10.1007/s11571-013-9267-8

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Twitter Trends Help Researchers Forecast Viral Memes

Twitter Trends Help Researchers Forecast Viral Memes | Papers | Scoop.it

What makes a meme— an idea, a phrase, an image—go viral? For starters, the meme must have broad appeal, so it can spread not just within communities of like-minded individuals but can leap from one community to the next. Researchers, by mining public Twitter data, have found that a meme's “virality” is often evident from the start. After only a few dozen tweets, a typical viral meme (as defined by tweets using a given hashtag) will already have caught on in numerous communities of Twitter users. In contrast, a meme destined to peter out will resonate in fewer groups.

 


Via Claudia Mihai
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june holley's curator insight, January 23, 2014 8:31 AM

Some important ideas here for people interested in change.

Premsankar Chakkingal's curator insight, January 30, 2014 8:58 AM

Forecasting the Future Twitter Trends in hashtags

Christian Verstraete's curator insight, February 3, 2014 4:48 AM

Twitter, what happens when things go viral?

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How Can the Study of Complexity Transform Our Understanding of the World?

How Can the Study of Complexity Transform Our Understanding of the World? | Papers | Scoop.it

The “study of complexity” refers to the attempt to find common principles underlying the behavior of complex systems—systems in which large collections of components interact in nonlinear ways. Here, the term nonlinear implies that the system can’t be understood simply by understanding its individual components; nonlinear interactions cause the whole to be “more than the sum of its parts.”


How Can the Study of Complexity Transform Our Understanding of the World?

Melanie Mitchell

https://www.bigquestionsonline.com/content/how-can-study-complexity-transform-our-understanding-world

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António F Fonseca's curator insight, January 22, 2014 4:45 AM

Wonderful and clarifying text.

Lorien Pratt's curator insight, January 22, 2014 11:20 PM

One of my favorite complexity authors.  An excerpt: "In the past it was widely assumed that such phenomena are hard to predict because the underlying processes are highly complex, and that random factors must play a key role.  However, Complex Systems science—especially the study of dynamics and chaos—have shown that complex behavior and unpredictability can arise in a system even if the underlying rules are extremely simple and completely deterministic.  Often, the key to complexity is the iteration over time of simple, though nonlinear, interaction rules among the system’s components."


This insight is at the core of Decision Intelligence, which adds an understanding of these emergent behaviors to the usual big data/predictive analytics/optimization stack.

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Haunted by His Brother, He Revolutionized Physics

Haunted by His Brother, He Revolutionized Physics | Papers | Scoop.it

Time. As a physicist, Wheeler had always been curious to untangle the nature of that mysterious dimension. But now, in the wake of Joe’s death, it was personal.
Wheeler would spend the rest of his life struggling against time. His journals, which he always kept at hand (and which today are stashed, unpublished, in the archives of the American Philosophical Society Library in Philadelphia), reveal a stunning portrait of an obsessed thinker, ever-aware of his looming mortality, caught in a race against time to answer not a question, but the question: “How come existence?”
“Of all obstacles to a thoroughly penetrating account of existence, none looms up more dismayingly than ‘time,’” Wheeler wrote. “Explain time? Not without explaining existence. Explain existence? Not without explaining time.”

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Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity

The human connectome has been widely studied over the past decade. A principal finding is that it can be decomposed into communities of densely interconnected brain regions. Past studies have often used single-scale modularity measures in order to infer the connectome's community structure, possibly overlooking interesting structure at other organizational scales. In this report, we used the partition stability framework, which defines communities in terms of a Markov process (random walk), to infer the connectome's multi-scale community structure. Comparing the community structure to observed resting-state functional connectivity revealed communities across a broad range of scales that were closely related to functional connectivity. This result suggests a mapping between communities in structural networks, models of influence-spreading and diffusion, and brain function. It further suggests that the spread of influence among brain regions may not be limited to a single characteristic scale.


Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity
RICHARD F. BETZEL, ALESSANDRA GRIFFA, ANDREA AVENA-KOENIGSBERGER, JOAQUÍN GOÑI, JEAN-PHILIPPE THIRAN, PATRIC HAGMANN, OLAF SPORNS
Network Science , Volume 1 , Issue 03 , December 2013, pp 353 - 373
http://dx.doi.org/10.1017/nws.2013.19

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On the biological and cultural evolution of shame: Using internet search tools to weight values in many cultures

Shame has clear biological roots and its precise form of expression affects social cohesion and cultural characteristics. Here we explore the relative importance between shame and guilt by using Google Translate to produce translation for the words shame, guilt, pain, embarrassment and fear to the 64 languages covered. We also explore the meanings of these concepts among the Yanomami, a horticulturist hunter-gatherer tribe in the Orinoquia. Results show that societies previously described as 'guilt societies' have more words for guilt than for shame, but the large majority, including the societies previously described as 'shame societies', have more words for shame than for guilt. Results are consistent with evolutionary models of shame which predict a wide scatter in the relative importance between guilt and shame, suggesting that cultural evolution of shame has continued the work of biological evolution, and that neither provides a strong adaptive advantage to either shame or guilt. We propose that the study of shame will improve our understanding of the interaction between biological and cultural evolution in the evolution of cognition and emotions.


On the biological and cultural evolution of shame: Using internet search tools to weight values in many cultures
Klaus Jaffe, Astrid Florez, Cristina M Gomes, Daniel Rodriguez, Carla Achury

http://arxiv.org/abs/1401.1100

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